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Genetic Algorithm for Decentralized PI Controller Tuning of a Multi-Span Web Transport System Based on Overlapping Decomposition

机译:基于重叠分解的遗传算法在分散式PI控制器优化中的应用

摘要

The use of multi-span web transport systems often requires dedicating a particular effort for defining a control system able to protect the integrity of the web. In web handling processes there is a clear need for controlling web velocity and tension. As for any control problem, the best results are achieved when there is a clear understanding of the controlled process. Starting from a new mathematical model called Transfer Matrix Model for a more accurate description of a web transport system, an optimization study for identifying parameters of the PI controllers for a decentralized multiinput and multi-output system (MIMO) has been proposed. The possibility of using PI controllers for each section is attractive considering that an overlapping system decomposition may permit to take into account the mutual interaction of the neighbor sections reaching specified performance objectives. Finally, by using a nonlinear interpolation of the trend of a preliminary database of values obtained through genetic algorithm, a self-tuning strategy is proposed to estimate optimal PI parameters under certain conditions, avoiding the long identification process and making the system flexible and adaptive. Simulations and experimental results validate and illustrate the effectiveness and the simplicity of the proposed method by considering several different set-points.
机译:多跨度幅材传输系统的使用通常需要专门的努力来定义能够保护幅材完整性的控制系统。在幅材处理过程中,显然需要控制幅材的速度和张力。对于任何控制问题,只要对受控过程有清楚的了解,就能获得最佳结果。为了更准确地描述Web传输系统,从称为传输矩阵模型的新数学模型开始,提出了一种用于识别分散式多输入多输出系统(MIMO)的PI控制器参数的优化研究。考虑到重叠的系统分解可能允许考虑达到指定性能目标的相邻部分的相互交互,因此对于每个部分使用PI控制器的可能性很有吸引力。最后,通过对通过遗传算法获得的初始值数据库的趋势进行非线性插值,提出了一种自整定策略,可以在一定条件下估计最佳PI参数,从而避免了冗长的识别过程,并使系统具有灵活性和自适应性。仿真和实验结果通过考虑几个不同的设定点验证并说明了该方法的有效性和简便性。

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